Compare AI models
| Specifications | ||
ParametersThe learned values that shape how a model responds. B means billion and T means trillion. For mixture-of-experts models, the total count is larger than the number active for each token. Parameter count alone does not measure quality. | 7B/67B | — |
Context windowHow much information the model can work with in one request, measured in tokens — pieces of words or other data. This includes your question, attachments, conversation and reply. Limits can vary by model variant and provider. | 4k | 32k |
| Overview | ||
| Company | DeepSeek | Qwen |
| Release date | Nov 29 2023 | Jan 28 2025 |
| Access | Open Weight | Closed |
| Model details | View model | View model |
Other comparisons
DeepSeek-LLMvsClaude Haiku 5.5Qwen2.5-MaxvsClaude Haiku 5.5DeepSeek-LLMvsGPT-6.1 SolQwen2.5-MaxvsGPT-6.1 SolDeepSeek-LLMvsGemini 4 ArgonQwen2.5-MaxvsGemini 4 ArgonDeepSeek-LLMvsMuse Spark OpenQwen2.5-MaxvsMuse Spark OpenDeepSeek-LLMvsGrok 4.7Qwen2.5-MaxvsGrok 4.7DeepSeek-LLMvsMistral Large 4Qwen2.5-MaxvsMistral Large 4Frequently asked questions
DeepSeek-LLM and Qwen2.5-Max don't publish scores on any of the same benchmarks, so there's no direct head-to-head comparison. DeepSeek-LLM shipped 426 days before Qwen2.5-Max, so benchmark comparisons should account for the intervening progress.
Context windows are 4k (DeepSeek-LLM) vs 32k (Qwen2.5-Max). DeepSeek-LLM is open weight, while Qwen2.5-Max is closed.
Direct benchmark comparisons are unavailable — DeepSeek-LLM and Qwen2.5-Max don't publish scores on any of the same benchmarks.